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Journal of Computational Neuroscience

, Volume 42, Issue 1, pp 1–10 | Cite as

Twenty years of ModelDB and beyond: building essential modeling tools for the future of neuroscience

  • Robert A. McDougal
  • Thomas M. Morse
  • Ted Carnevale
  • Luis Marenco
  • Rixin Wang
  • Michele Migliore
  • Perry L. Miller
  • Gordon M. Shepherd
  • Michael L. Hines
Article

Abstract

Neuron modeling may be said to have originated with the Hodgkin and Huxley action potential model in 1952 and Rall’s models of integrative activity of dendrites in 1964. Over the ensuing decades, these approaches have led to a massive development of increasingly accurate and complex data-based models of neurons and neuronal circuits. ModelDB was founded in 1996 to support this new field and enhance the scientific credibility and utility of computational neuroscience models by providing a convenient venue for sharing them. It has grown to include over 1100 published models covering more than 130 research topics. It is actively curated and developed to help researchers discover and understand models of interest. ModelDB also provides mechanisms to assist running models both locally and remotely, and has a graphical tool that enables users to explore the anatomical and biophysical properties that are represented in a model. Each of its capabilities is undergoing continued refinement and improvement in response to user experience. Large research groups (Allen Brain Institute, EU Human Brain Project, etc.) are emerging that collect data across multiple scales and integrate that data into many complex models, presenting new challenges of scale. We end by predicting a future for neuroscience increasingly fueled by new technology and high performance computation, and increasingly in need of comprehensive user-friendly databases such as ModelDB to provide the means to integrate the data for deeper insights into brain function in health and disease.

Keywords

Model sharing Model analysis Model discovery Reproducibility Neuroinformatics 

Notes

Acknowledgments

This project was supported by the National Institutes of Health (NIH) grants R01 DC009977 from the National Institute on Deafness and Other Communication Disorders (NIDCD) and T15 LM007056 from the National Library of Medicine (NLM). We are grateful for platforms provided to us for the curation of ModelDB models including the Louise cluster (part of Yale’s HPC facilities operated by the Yale Center for Research Computing and Yale’s W.M. Keck Biotechnology Laboratory, funded by NIH grants: RR19895 and RR029676-01) and the Neuroscience Gateway (NSG) Portal (Sivagnanam et al. 2013) supported by the National Science Foundation.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Robert A. McDougal
    • 1
  • Thomas M. Morse
    • 1
  • Ted Carnevale
    • 1
  • Luis Marenco
    • 1
    • 2
    • 3
  • Rixin Wang
    • 3
    • 4
  • Michele Migliore
    • 1
    • 5
  • Perry L. Miller
    • 2
    • 3
    • 4
  • Gordon M. Shepherd
    • 1
  • Michael L. Hines
    • 1
  1. 1.Department of NeuroscienceYale UniversityNew HavenUSA
  2. 2.VA Connecticut Healthcare SystemWest HavenUSA
  3. 3.Center for Medical InformaticsYale UniversityNew HavenUSA
  4. 4.Department of AnesthesiologyYale UniversityNew HavenUSA
  5. 5.Institute of Biophysics, National Research CouncilPalermoItaly

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